375 results — topic: Snow & Ice

Dataset

Phenological responses to climate change do not exhibit phylogenetic signal in a subalpine plant community

Phylogenetic relationships may underlie species-specific phenological sensitivities to abiotic variation and may help to predict these responses to climate change. Although shared evolutionary history may mediate both phenology and phenological sensitivity to abiotic variation, few studies have expl

CaraDonna, Paul J, Inouye, David W2021DOI: 10.6084/m9.figshare.c.3307416.v1
Dataset

Flowering phenology in subalpine meadows: Does climate variation influence community co-flowering patterns?

Climate change is expected to alter patterns of species co-occurrence, in both space and time. Species-specific shifts in reproductive phenology may alter the assemblages of plant species in flower at any given time during the growing season. Temporal overlap in the flowering periods (co-flowering)

Forrest, Jessica, Inouye, David W, D. Thomson, James2021DOI: 10.6084/m9.figshare.c.3301874.v1
Dataset

Appendix B. Phenological shifts and phenological sensitivity to snowmelt date and summer temperature data used in analyses.

Phylogenetic relationships may underlie species-specific phenological sensitivities to abiotic variation and may help to predict these responses to climate change. Although shared evolutionary history may mediate both phenology and phenological sensitivity to abiotic variation, few studies have expl

CaraDonna, Paul J, Inouye, David W2021DOI: 10.6084/m9.figshare.3561351.v1
Dataset

Depth profiles of soil CO2 Concentrations, soil temperature, and soil moisture (Rocky Mountain Biological Laboratory, Gothic, Colorado, 2011-2016)

Soil respiration (the flux of CO2 from the soil surface) is one of the largest and most variable fluxes in the global carbon cycle, and yet also one of the least understood, primarily due to methodological difficulties. These are (1) measuring soil respiration at high temporal frequencies and (2) at

Carbone, Mariah2021DOI: 10.6084/m9.figshare.7834406.v1
Dataset

Bee phenology is predicted by climatic variation and functional traits

Climate change is shifting the environmental cues that determine the phenology of interacting species. Plant-pollinator systems may be susceptible to temporal mismatch if bees and flowering plants differ in their phenological responses to warming temperatures. While the cues that trigger flowering a

Stemkovski, Michael2021DOI: 10.5061/dryad.t76hdr7zcCited 2 times
Dataset

Phenological responses to multiple environmental drivers under climate change: insights from a long-term observational study and a manipulative field experiment

Climate change has induced pronounced shifts in the reproductive phenology of plants, yet we know little about which environmental factors contribute to interspecific variation in responses and their effects on fitness. We integrate data from a 43-year record of first flowering for six species in su

Wadgymar, Susana M.2021DOI: 10.5061/dryad.qr5vdCited 1 times
Dataset

Frost sensitivity of leaves and flowers of subalpine plants is related to tissue type and phenology

Harsh abiotic conditions such as low temperatures that lead to spring and summer frost events in high-elevation and high-latitude ecosystems can have strong negative consequences for plant growth, survival, and reproduction. Despite the predicted increase in episodic frost events under continued cli

CaraDonna, Paul J, Bain, Justin A2021DOI: 10.5061/dryad.v4cv6Cited 1 times
Dataset

Phenotypic plasticity and adaptive evolution contribute to advancing flowering phenology in response to climate change

Anthropogenic climate change has already altered the timing of major life history transitions, such as the initiation of reproduction. Both phenotypic plasticity and adaptive evolution can underlie rapid phenological shifts in response to climate change but their relative contributions are poorly un

Anderson, Jill T.2021DOI: 10.5061/dryad.68mj4Cited 1 times
Dataset

End-Member Mixing Analysis Data Package for the East River Watershed, CO USA.

The data package consolidates water year 2016 stream, rain, snow and groundwater data used by Carroll et al. (2018) for end-member mixing analysis to isolate seasonal stream source within the East River, CO. Stream concentration and daily discharge are provided for the 11 sub-basins of the East Rive

Carroll R, Williams K, Bill M2021DOI: 10.21952/WTR/1465929
Dataset

Annual floodplain sediment deposition recorded using feldspar clay marker horizons along the East River, Colorado, 2015-2017.

White feldspar clay was placed along 24 transects defining a ~9-km long study reach along the meandering snowmelt-dominated East River in Colorado, USA. Feldspar markers horizons were placed in the fall of 2015 and 2016 along transects with the space between them increasing with distance from the ch

Sutfin N, Rowland J2021DOI: 10.15485/1577279
Dataset

Sample Collection Metadata for Soil Cores from the East River Watershed, Colorado collected in 2017.

This data package contains sample collection metadata for soil cores from the East River Watershed in Colorado used in biogeochemical analyses by the Watershed Function SFA. Soil cores were collected seasonally during autumn, winter, snowmelt, and spring at a predominately montane meadow, high altit

Sorensen P, Brodie E, Beller H2021DOI: 10.21952/WTR/1573029Cited 2 times
Dataset

Soil Nitrogen, Water Content, Microbial Biomass, and Archaeal, Bacterial and Fungal Communities from the East River Watershed, Colorado collected in 2016-2017.

This data set contains soil measurements made at the Pumphouse Hillslope to Floodplain transect at the locations of the early snowmelt-timing manipulation experiments in the East River Watershed in Colorado, USA. The data were collected in 2016 and 2017 to determine soil microbial responses to snow

Sorensen P, Brodie E, Beller H2021DOI: 10.15485/1577267Cited 3 times
Dataset

Hyporheic, Floodplain, and Surface Water (on Floodplain and River) Geochemical Datasets, and Shapefiles on Meander C at the East River, Colorado.

The purpose of this dataset was to sample surface water and groundwater geochemistry at random locations in the East River, Colorado to provide a broad spatial dataset of geochemistry. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River

Newcomer M, Raberg J, Dwivedi D2021DOI: 10.15485/1647038
Dataset

Total Dissolved Nitrogen and Ammonia Data for the East River Watershed, Colorado (2015-2022)

This data package contains mean values for total dissolved nitrogen (TDN) and ammonia concentrations for water samples taken from the East River Watershed in Colorado. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United Sta

Dong W, Beutler C, Bouskill N2021DOI: 10.15485/1660456
Dataset

1 m Resolution Basic Landcover Map for the Upper Gunnison Domain Derived from NAIP Imagery and LiDAR

This is 1 meter resolution landcover map developed for the RMBL Spatial Data Platform. Source datasets include 2017 and 2019 4-band imagery from the National Aerial Imagery Program, and 2019 LiDAR data collected by Quantum Geospatial for the Colorado Hazard Mapping Program. The numeric codes for the

Ian Breckheimer2021
Dataset

Snow Depth on April 7th 2019 for Upper East River Derived from Airborne Snow Observatory Data

This is a 3m map of snow depth derived from repeat LiDAR data collection by the Airborne Snow Observatory. This dataset has been clipped and resampled to the standard 3m SDP grid, and is derived directly from: Painter, T. 2018. ASO L4 Lidar Snow Depth 3m UTM Grid, Version 1. Boulder, Colorado USA. N

Painter, T2021DOI: 10.5067/KIE9QNVG7HP0Cited 3 times
Dataset

Snow Depth on March 31st 2018 for Upper East River Derived from Airborne Snow Observatory Data

This is a 3m map of snow depth derived from repeat LiDAR data collection by the Airborne Snow Observatory. This dataset has been clipped and resampled to the standard 3m SDP grid, and is derived directly from: Painter, T. 2018. ASO L4 Lidar Snow Depth 3m UTM Grid, Version 1. Boulder, Colorado USA. N

Painter, T2021DOI: 10.5067/KIE9QNVG7HP0Cited 3 times
Dataset

Winter Travel Time from Crested Butte for the Upper East River Domain

This map represents the estimated on-road and off-road travel time in minutes from Crested Butte via the fastest travel means available (snowmobiles excluded). Estimates apply for winter (snow-on) conditions. This map was generated with the cost distance GRASS GIS module (r.cost) using estimated tra

Ian Breckheimer2021
Dataset

Summer Travel Time from Gothic for the Upper East River Domain

This map represents the estimated on-road and off-road travel time in minutes from Crested Butte via the fastest travel means available (snowmobiles excluded). Estimates apply for summer (snow-off) conditions after all roads have been opened to vehicle traffic. This map was generated with the cost d

Ian Breckheimer2021
Dataset

Styled 2019 snow depth basemap of the Upper East River domain

This is a styled basemap showing snow depth on April 7th 2019 derived from repeat LiDAR data collection by the Airborne Snow Observatory. This dataset is derived directly from: Painter, T. 2019. ASO L4 Lidar Snow Depth 3m UTM Grid, Version 1. Boulder, Colorado USA. NASA National Snow and Ice Data Ce

Ian Breckheimer2021